David Sathuluri is a Research Associate and Dr. Marco Tedesco is a Lamont Research Professor at the Lamont-Doherty Earth Observatory of Columbia University.
As climate scientists warn that we are approaching irreversible tipping points in the Earth’s climate system, paradoxically the very technologies being deployed to detect these tipping points – often based on AI – are exacerbating the problem, via acceleration of the associated energy consumption.
The UK’s much-celebrated £81-million ($109-million) Forecasting Tipping Points programme involving 27 teams, led by the Advanced Research + Invention Agency (ARIA), represents a contemporary faith in technological salvation – yet it embodies a profound contradiction. The ARIA programme explicitly aims to “harness the laws of physics and artificial intelligence to pick up subtle early warning signs of tipping” through advanced modelling.
We are deploying massive computational infrastructure to warn us of climate collapse while these same systems consume the energy and water resources needed to prevent or mitigate it. We are simultaneously investing in computationally intensive AI systems to monitor whether we will cross irreversible climate tipping points, even as these same AI systems could fuel that transition.
The computational cost of monitoring
Training a single large language model like GPT-3 consumed approximately 1,287 megawatt-hours of electricity, resulting in 552 metric tons of carbon dioxide – equivalent to driving 123 gasoline-powered cars for a year, according to a recent study.
GPT-4 required roughly 50 times more electricity. As the computational power needed for AI continues to double approximately every 100 days, the energy footprint of these systems is not static but is exponentially accelerating.
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And the environmental consequences of AI models extend far beyond electricity usage. Besides massive amounts of electricity (much of which is still fossil-fuel-based), such systems require advanced cooling that consumes enormous quantities of water, and sophisticated infrastructure that must be manufactured, transported, and deployed globally.
The water-energy nexus in climate-vulnerable regions
A single data center can consume up to 5 million gallons of drinking water per day – sufficient to supply thousands of households or farms. In the Phoenix area of the US alone, more than 58 data centers consume an estimated 170 million gallons of drinking water daily for cooling.
The geographical distribution of this infrastructure matters profoundly as data centers requiring high rates of mechanical cooling are disproportionately located in water-stressed and socioeconomically vulnerable regions, particularly in Asia-Pacific and Africa.
At the same time, we are deploying AI-intensive early warning systems to monitor climate tipping points in regions like Greenland, the Arctic, and the Atlantic circulation system – regions already experiencing catastrophic climate impacts. They represent thresholds that, once crossed, could trigger irreversible changes within decades, scientists have warned.
Yet computational models and AI-driven early warning systems operate according to different temporal logics. They promise to provide warnings that enable future action, but they consume energy – and therefore contribute to emissions – in the present.
This is not merely a technical problem to be solved with renewable energy deployment; it reflects a fundamental misalignment between the urgency of climate tipping points and the gradualist assumptions embedded in technological solutions.
The carbon budget concept reveals that there is a cumulative effect on how emissions impact on temperature rise, with significant lags between atmospheric concentration and temperature impact. Every megawatt-hour consumed by AI systems training on climate models today directly reduces the available carbon budget for tomorrow – including the carbon budget available for the energy transition itself.
The governance void
The deeper issue is that governance frameworks for AI development have completely decoupled from carbon budgets and tipping point timescales. UK AI regulation focuses on how much computing power AI systems use, but it does not require developers to ask: is this AI’s carbon footprint small enough to fit within our carbon budget for preventing climate tipping points?
There is no mechanism requiring that AI infrastructure deployment decisions account for the specific carbon budgets associated with preventing different categories of tipping points.
Meanwhile, the energy transition itself – renewable capacity expansion, grid modernization, electrification of transport – requires computation and data management. If we allow unconstrained AI expansion, we risk the perverse outcome in which computing infrastructure consumes the surplus renewable energy that could otherwise accelerate decarbonization, rather than enabling it.
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What would it mean to resolve the paradox?
Resolving this paradox requires, for example, moving beyond the assumption that technological solutions can be determined in isolation from carbon constraints. It demands several interventions:
First, any AI-driven climate monitoring system must operate within an explicitly defined carbon budget that directly reflects the tipping-point timescale it aims to detect. If we are attempting to provide warnings about tipping points that could be triggered within 10-20 years, the AI system’s carbon footprint must be evaluated against a corresponding carbon budget for that period.
Second, governance frameworks for AI development must explicitly incorporate climate-tipping point science, establishing threshold restrictions on computational intensity in relation to carbon budgets and renewable energy availability. This is not primarily a “sustainability” question; it is a justice and efficacy question.
Third, alternative models must be prioritized over the current trajectory toward ever-larger models. These should include approaches that integrate human expertise with AI in time-sensitive scenarios, carbon-aware model training, and using specialized processors matched to specific computational tasks rather than relying on universal energy-intensive systems.
The deeper critique
The fundamental issue is that the energy-system tipping point paradox reflects a broader crisis in how wealthy nations approach climate governance. We have faith that innovation and science can solve fundamental contradictions, rather than confronting the structural need to constrain certain forms of energy consumption and wealth accumulation. We would rather invest £81 million in computational systems to detect tipping points than make the political decisions required to prevent them.
The positive tipping point for energy transition exists – renewable energy is now cheaper than fossil fuels, and deployment rates are accelerating. What we lack is not technological capacity but political will to rapidly decarbonize, as well as community participation.
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Deploying energy-intensive AI systems to monitor tipping points while simultaneously failing to deploy available renewable energy represents a kind of technological distraction from the actual political choices required.
The paradox is thus also a warning: in the time remaining before irreversible tipping points are triggered, we must choose between building ever-more sophisticated systems to monitor climate collapse or deploying available resources – capital, energy, expertise, political attention – toward allaying the threat.
The post Using energy-hungry AI to detect climate tipping points is a paradox appeared first on Climate Home News.
Using energy-hungry AI to detect climate tipping points is a paradox
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The planet is heating up more quickly than ever before.
For decades, greenhouse gas emissions caused by human activity have been building up in the atmosphere and trapping ever-higher levels of heat.
The resulting asymmetry between incoming solar energy and energy radiated back out into space – known as “Earth’s energy imbalance” – provides a direct measure of the extent to which humans are disrupting the Earth’s climate system.
This imbalance is growing and in 2025 its 10-year average reached a record high, indicating that global temperatures could increase at even higher rates in the future.
This is among the headline findings of the latest “indicators of global climate change” (IGCC) report, published in the journal Earth System Science Data, which tracks changes in the climate system on an annual basis.
The report, now in its fourth iteration, has been produced by dozens of scientists from around the world.
Its findings are designed to fill the gap between Intergovernmental Panel on Climate Change (IPCC) science reports, which are published every 5-7 years.
In this article, we unpack the IGCC report, which explores how human activity is driving a growing energy imbalance and why monitoring systems to track global climate are so crucial.
(For more on previous IGCC reports, see Carbon Brief’s coverage in 2023, 2024 and 2025.)
Greenhouse gas emissions remain at an all-time high
Global greenhouse gas emissions are continuing to increase, mostly as a result of the use of fossil fuels. However, deforestation, agriculture and industrial processes also play an important role.
Over the most recent decade (2015-24), emissions stood at the equivalent of 54.6bn tonnes of carbon dioxide equivalent (GtCO2e) per year. In 2024, the most recent year for which we have complete data, emissions reached 56.8GtCO2e.
As the chart below shows, these emissions have pushed up atmospheric levels of CO2, methane and nitrous oxide. In 2025, concentrations of these gases reached 425.6 parts per million (ppm), 1936.3 parts per billion (ppb) and 339.4ppb, respectively.
This represents a rise of 3.8%, 3.8% and 2.2%, respectively, since the 2019 levels reported in the IPCC’s sixth assessment report (AR6).
At the same time, declines in emissions of aerosols such as sulphur dioxide, partly as a result of efforts to tackle air pollution, are increasing the Earth’s energy imbalance. This is because aerosols have a cooling effect on the Earth’s climate, counteracting warming from CO2 and other greenhouse gas emissions.
(Tackling sulphur dioxide, alongside other particulate emissions, remains critical because the immediate health and environmental damage they cause far outweighs their short-term cooling effect on the climate.)
The Earth’s energy imbalance is rising rapidly
The Earth’s energy imbalance has long been recognised as a key indicator of how the climate is being affected by human activities.
However, it is only in the last few decades that scientists have been able to record temperature changes deep enough in the ocean to accurately quantify it.
Earth’s energy imbalance measures how quickly excess heat is accumulating in every part of the Earth system, primarily in the ocean, but also in land, ice and atmosphere.
Through this accumulation of heat, the energy imbalance influences the rate of sea level rise and ice melt across the world, as well as increasing the frequency and intensity of extreme weather events, such as storms, floods and droughts.
Without human influence, the Earth’s energy imbalance would be close to zero.
But, as greenhouse gas emissions have built up in the atmosphere, the imbalance has been growing since the 1970s. Recent increases to Earth’s energy imbalance have outpaced those projections made by climate models — indicating the planet could see more warming than expected in the future.
As the right-hand chart below shows, the imbalance is now at a record high, having more than doubled over the past two decades.
It has increased by around 40% since 2019, from an average 0.79 watts per square metre (Wm2) over 2006-18, according to IPCC AR6, to 1.12Wm2 over 2013-25.
The left-hand chart shows how heat is accumulating in the ocean (blues), ice (grey), land (orange) and atmosphere (purple).
Global temperature rise
The excess heat building up in the climate system from the energy imbalance is pushing up global temperatures at a record rate of 0.27C per decade.
We estimate that human-induced warming – the amount of observed global surface
temperature increase attributable to both the direct and indirect effects of human activities – reached 1.37C in 2025. This has risen from 1.0C in 2017, as reported in IPCC AR6.
While natural variability in the climate system – such as El Niño or La Niña events – can also influence temperatures year-to-year, the upward temperature trend we are seeing is being driven by the persistent imbalance in energy.
We now expect global temperatures to exceed the Paris Agreement limit of 1.5C above pre-industrial levels around the year 2030.
This is significant because 1.5C has been identified as the critical dividing line between manageable climate risks and catastrophic, potentially irreversible damage to global ecosystems and human societies.
Heat accumulating throughout the Earth system
While heat is accumulating throughout the Earth system, it is not being distributed evenly around the globe.
Since the 1970s, around 90% of this heat has been taken up by the ocean, affecting marine ecosystems, ocean circulation patterns, sea level rise and climate extremes.
For example, the number of marine heatwave days – periods of unusually high sea surface temperatures – has more than tripled globally since the early 1990s. The year 2025 alone saw 65 days of marine heatwaves – meaning they occurred, on average, more than one day a week.
Meanwhile, the cryosphere – the portion of the Earth made up of frozen water, including glaciers, ice sheets and permafrost – is experiencing widespread ice loss and thawing in response to the growing energy imbalance. This affects ecosystems, sea level rise and infrastructure in polar and high-latitude regions.
Rapid warming has also resulted in record extreme temperatures over land, with average maximum temperatures for any single day over 2016-25 around 1.92C above pre-industrial levels). This is an increase of almost half a degree compared to the previous decade (2006-15).
Sea level rise and the energy imbalance
Sea level rise provides one of the clearest long-term signals of a changing planet.
It is closely linked to Earth’s energy imbalance. As heat accumulates in the ocean, water expands, raising sea levels. Meanwhile, a warming land and atmosphere means addition of water to the oceans through melting of glaciers and ice sheets, also adding to sea level rise.
Over the long-term, sea levels have been rising, on average, at a rate of around 1.8mm per year since 1901, totalling a record 23cm in 2025. This is increasing the risk of coastal flooding, erosion and habitat loss in many low-lying areas around the world.
This rise can be seen in the left-hand chart below, which shows observed global sea level changes from tide gauges (grey and blue dashed lines) and satellites (red dashed lines) since 1901. The solid lines indicate the average across multiple datasets.
Sea level rise is accelerating consistent with the observed increase in Earth’s energy imbalance. Over 2006-25, sea levels have risen at a rate of 3.67mm per year – more than double the rate of 1.69mm per year seen over 1976-95.
This increasing rate is shown in the right-hand figure below, which shows four successive overlapping 20-year periods and the most-recent decade.
(Last year’s transition from El Niño to weak La Niña conditions affected global rainfall patterns and led to a small and temporary fall in global average sea level in 2025. This explains the slight decrease in rate of sea level rise for the most recent decade, which is affected more than the 20-year period 2006-25.)
The bigger picture
Despite greenhouse gas emissions not increasing as rapidly as in the 2000s, this year’s IGCC findings continue to show how far and how fast the climate is changing due to human activity.
A significant increase in decarbonisation efforts in the second half of this decade is required to slow down the rate of human-caused warming and limit the escalation of climate risks and impacts.
These findings, like many others produced by scientists across the globe, rely on international expertise, partnership and the maintenance and availability of global climate datasets and the global observing programmes that underpin them.
This year’s edition of IGCC used more than 40 global datasets produced by research teams around the world, including the NASA satellite record of the Earth’s energy imbalance and the ARGO deep ocean float network.
However, a number of long-term monitoring programmes could be threatened by funding decisions made by governments around the world, most notably the Trump administration in the US.
Local meteorological data and weather balloon measurement programmes in many countries have declined in recent years, especially in Africa, the west Pacific and South America. This reduces scientists’ ability to monitor and understand key indicators of climate change.
This is not just an issue for climate science. Many of these observations are key to weather forecasts and systems that provide early warning for extreme weather. For example, media reports have suggested that recent reductions in weather balloon measurements in Alaska led to a lack of warnings for a recent winter storm.
The continuity and integrity of the climate observations that scientists use to understand how the climate is changing depends on effective and sustained coordination by international organisations, such as the Global Climate Observing System, the World Meteorological Organization and World Climate Research Programme.
Without this data and its coordination, future assessments will be much more difficult at a time when urgent climate action is needed.
The post Guest post: How a record-high ‘energy imbalance’ is driving global warming appeared first on Carbon Brief.
Guest post: How a record-high ‘energy imbalance’ is driving global warming
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